{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 218,
   "id": "d5172971",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import math\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "from datetime import date\n",
    "import pandas_ta as ta\n",
    "from ta.volatility import BollingerBands\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "from yahoo_fin import stock_info as si\n",
    "import datetime\n",
    "from pandas.tseries.holiday import USFederalHolidayCalendar\n",
    "from pandas.tseries.offsets import CustomBusinessDay\n",
    "US_BUSINESS_DAY = CustomBusinessDay(calendar=USFederalHolidayCalendar())\n",
    "import fix_yahoo_finance as yf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "id": "78246c6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_historic_data(symbol):\n",
    "    today = datetime.date.today()\n",
    "    today_str = today.strftime(\"%Y-%m-%d\")\n",
    "    #  Get last year's data\n",
    "    start_date = today - (600 * US_BUSINESS_DAY)\n",
    "    start_date_str = datetime.datetime.strftime(start_date, \"%Y-%m-%d\")\n",
    "    # Download data from Yahoo Finance\n",
    "    try:\n",
    "        df = si.get_data(symbol, start_date=start_date_str, end_date=today_str, index_as_date=False)\n",
    "        return df\n",
    "    except:\n",
    "        print('Error loading stock data for ' + symbol)\n",
    "        return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "e2695801",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_smas(df):\n",
    "    df['SMA50'] = ta.sma(df[\"close\"], length=50)\n",
    "    df['SMA200'] = ta.sma(df[\"close\"], length=200)\n",
    "\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "id": "4a4811a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def determine_primary_market(df):\n",
    "    df['BEAR'] = np.where(df['SMA50'] < df[\"SMA200\"], df['close'], np.NaN)\n",
    "    df['BULL'] = np.where(df['SMA50'] > df[\"SMA200\"], df['close'], np.NaN) \n",
    "\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6f89335",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "id": "b1f4bd5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_graph(df):\n",
    "    fig = make_subplots(rows=1, cols=1)\n",
    "\n",
    "    #  Plot close price\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['close'], line=dict(color=\"blue\", width=1), name=\"Close\"), row = 1, col = 1)\n",
    "    \n",
    "    #  Plot SMAs\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['SMA50'], line=dict(color=\"green\", width=1), name=\"SMA50\"), row = 1, col = 1)\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['SMA200'], line=dict(color=\"red\", width=1), name=\"SMA200\"), row = 1, col = 1)\n",
    "    \n",
    "    \n",
    "    # Primary Markets\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['BULL'], line=dict(color=\"green\", width=1), name=\"Bull\"), row = 1, col = 1)\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['BEAR'], line=dict(color=\"red\", width=1), name=\"Bear\"), row = 1, col = 1)\n",
    "    \n",
    "    fig.update_layout(\n",
    "        title={'text':'Primary Markets', 'x':0.5},\n",
    "        autosize=False,\n",
    "        width=800,height=400)\n",
    "    fig.update_yaxes(range=[0,1000000000],secondary_y=True)\n",
    "    fig.update_yaxes(visible=False, secondary_y=True)  #hide range slider\n",
    "    \n",
    "    fig.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "7b51503d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\dutch\\anaconda3\\envs\\tradesystem1\\lib\\site-packages\\plotly\\graph_objs\\_deprecations.py:378: DeprecationWarning:\n",
      "\n",
      "plotly.graph_objs.Line is deprecated.\n",
      "Please replace it with one of the following more specific types\n",
      "  - plotly.graph_objs.scatter.Line\n",
      "  - plotly.graph_objs.layout.shape.Line\n",
      "  - etc.\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
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     "metadata": {},
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    }
   ],
   "source": [
    "df = load_historic_data('NDX')\n",
    "df = calculate_smas(df)\n",
    "df = determine_primary_market(df)\n",
    "plot_graph(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "d0fbaef7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#  Index Calculation\n",
    "def load_crypto_data(symbols):\n",
    "    today = datetime.date.today()\n",
    "    today_str = today.strftime(\"%Y-%m-%d\")\n",
    "    #  Get last year's data\n",
    "    start_date = today - (600 * US_BUSINESS_DAY)\n",
    "    start_date_str = datetime.datetime.strftime(start_date, \"%Y-%m-%d\")\n",
    "    # Download data from Yahoo Finance\n",
    "    try:\n",
    "        df = si.get_data(symbols, start_date=start_date_str, end_date=today_str, index_as_date=False)\n",
    "        return df\n",
    "    except:\n",
    "        print('Error loading stock data for ' + symbols)\n",
    "        return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "0040b2f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  3 of 3 completed\n",
      "Date\n",
      "2021-05-01    1.025609\n",
      "2021-05-02    1.002909\n",
      "2021-05-03    1.020647\n",
      "2021-05-04    1.018919\n",
      "2021-05-05    1.130237\n",
      "                ...   \n",
      "2022-04-24    0.480810\n",
      "2022-04-25    0.487341\n",
      "2022-04-26    0.450578\n",
      "2022-04-27    0.458952\n",
      "2022-04-28    0.457430\n",
      "Name: CRYPTO_INDEX, Length: 363, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "symbols = ['XLM-USD','DOGE-USD','STX-USD']\n",
    "\n",
    "start = datetime.datetime(2021,5,1)\n",
    "end = datetime.datetime(2022,4,29)\n",
    "crypto_df = yf.download(symbols, start=start, end=end)\n",
    "#print(crypto_df.head())\n",
    "#\n",
    "#\n",
    "#  Convert columns from tuple to strings\n",
    "crypto_df.columns = ['{}_{}'.format(x[0], x[1]) for x in crypto_df.columns]\n",
    "#for (columnName, columnData) in crypto_df.iteritems():\n",
    "#    print('Column Name : ', columnName)\n",
    "column_names = ['Close_STX-USD', 'Close_DOGE-USD', 'Close_XLM-USD']  \n",
    "crypto_df['CRYPTO_INDEX']= crypto_df[column_names].sum(axis=1) / len(symbols)\n",
    "print(crypto_df['CRYPTO_INDEX'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "id": "b25427ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_crypto_index(df):\n",
    "    fig = make_subplots(rows=1, cols=1)\n",
    "\n",
    "    #  Plot close price\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['CRYPTO_INDEX'], line=dict(color=\"blue\", width=2), name=\"Crypto Index\"), row = 1, col = 1)\n",
    "    \n",
    "    #  Plot Coins\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['Close_STX-USD'], line=dict(color=\"red\", width=1), name=\"STX-USD\"), row = 1, col = 1)\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['Close_DOGE-USD'], line=dict(color=\"yellow\", width=1), name=\"DOGE-USD\"), row = 1, col = 1)\n",
    "    fig.add_trace(go.Line(x = df.index, y = df['Close_XLM-USD'], line=dict(color=\"purple\", width=1), name=\"XLM-USD\"), row = 1, col = 1)\n",
    " \n",
    "    fig.update_layout(\n",
    "        title={'text':'Primary Markets', 'x':0.5},\n",
    "        autosize=False,\n",
    "        width=800,height=400)\n",
    "    fig.update_yaxes(range=[0,1000000000],secondary_y=True)\n",
    "    fig.update_yaxes(visible=False, secondary_y=True)  #hide range slider\n",
    "    \n",
    "    fig.show()"
   ]
  },
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   "execution_count": 227,
   "id": "345ab88d",
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\dutch\\anaconda3\\envs\\tradesystem1\\lib\\site-packages\\plotly\\graph_objs\\_deprecations.py:378: DeprecationWarning:\n",
      "\n",
      "plotly.graph_objs.Line is deprecated.\n",
      "Please replace it with one of the following more specific types\n",
      "  - plotly.graph_objs.scatter.Line\n",
      "  - plotly.graph_objs.layout.shape.Line\n",
      "  - etc.\n",
      "\n",
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